1b.Approach (from AD-416)
The project will define and characterize the organization and structure of the soybean genome and the genomes of other legumes with special emphasis on genes and gene families that underlie important agronomic and developmental traits. Hydroponics and global gene expression tools will be used to identify genes differentially expressed during iron stress conditions. Affymetrix GeneChips will be used to identify genes involved in yield, seed composition and other important traits in soybean. Bioinformatics will be used to position these genes on the whole genome sequence and the genetic map. Bioinformatic and experimental approaches will be used to identify and map genes differentially expressed during defense response and to identify and map defensin-like genes. A set of comparative molecular-evolutionary protocols will be used to make systematic and integrated use of large amounts of new genomic and functional data. Analyses will include comparison of homeologous regions, phylogenetic comparisons, and annotation of specific genomic regions.

3.Progress Report
We grew iron efficient and inefficient genotypes in iron depleted and iron replete hydroponic solutions. Tissue from each line was harvested. Root and stem tissue was provided to collaborators at ARS, St. Paul, MN, and leaf tissue was retained at ARS, Ames, IA. Using microarray analyses, we have identified candidate Iron Deficiency Chlorosis (IDC) genes that are differentially expressed in response to iron stress. We have aligned these genes with the recently released soybean genome sequence and have identified the protein-coding and regulatory regions. We have designed primers that span these regions and can be used to amplify them from the DNA of eight different genotypes representing iron efficient and iron inefficient soybean lines. Sequencing and alignment of the amplified product from each gene will identify single nucleotide polymorphisms (SNPs) that can be used for marker development. Thus far, we have used 106 primer pairs to amplify and sequence candidate genes from the eight genotypes. This corresponds to 848 individual sequences. The sequences for each region from each genotype have been aligned and compared. Forty-one SNPs have been identified to date. These SNPs represent 25 individual candidates. The boundaries of a high seed protein Quantitative Trait Loci (QTL) region were defined using molecular markers. A Bactieral Artificial Chromosome (BAC) physical map was developed across this QTL region. Using the whole genome sequence 374 SSRs were identified within this region. Fifty were polymorphic between high and low protein parents. The markers were used to more precisely define the location of the gene(s) responsible for the high protein phenotype. In an initial survey, we identified over 100 defensin-like genes from the unassembled soybean genome. We are in the process of screening the assembled soybean genome for additional defensin-like genes. We are particularly interested in the evolution of nodule and seed-specific defensins. We have recently finished sequencing the regions containing the candidate ASR resistance genes Rpp2 and Rpp4. The Rpp2 region contains 23 candidate resistance genes with homology to two known classes of disease resistance genes. The Rpp4 region contains three candidate resistance genes. We are now in the process of developing DNA constructs for use in Virus Induced Gene Silencing (VIGS). VIGS is a molecular technique that can be used to turn off gene expression in a live plant. Thus far we have developed four silencing constructs for Rpp4 and are in the process of developing four constructs for Rpp2. This research fits within NP 301 Action Plan Component 2: Crop Informatics, Genomics and Genetic Analyses, Problem Statement 2C: Genetic Analyses and Mapping of Important Traits because great progress has been made to identify genes that impart disease resistance in soybean.

4.Accomplishments
1.
Identifying genes for iron deficiency chlorosis (IDC). IDC results in millions of dollars in lost soybean production in the upper Midwest states. Soybean genotypes differ in their ability to adapt to iron limited conditions. Because of its quantitative character breeding advances for IDC are slow. Using global gene expression studies we have identified over 800 genes whose expression changes in response to iron deficiency. When we examine the biological roles of these genes, a clear pattern arises. Iron efficient plants turn on genes to aid in iron acquisition and to reduce plant stress. Iron inefficient plants are either unable to recognize that iron is limiting or cannot induce expression of the same genes. By taking advantage of the recently released soybean genome sequence, we could ‘map’ these genes on the soybean genome. Surprisingly, many of the genes were clustered together within the genome suggesting the expression of genes within a cluster were coordinately regulated. We are now developing markers surrounding these regions and will use them to more efficiently select soybeans that will produce better on IDC-sensitive soils. This will result in improved IDC-resistant cultivars released to the producers more quickly. This research fits within NP 301 Action Plant Component 2: Crop Informatics, Genomics and Genetic Analyses, Problem Statement 2C: Genetic Analyses and Mapping of Important Traits.

5.Significant Activities that Support Special Target Populations
None.